Description Details I. Formatting input data II. Model fitting and summary III. Model prediction and transformation of environmental data IV. Plotting model output and fitted functions Author(s)

Generalized Dissimilarity Modeling is a statistical technique for modelling spatial variation in biodiversity between pairs of geographical locations. The gdm package currently provides basic functions to fit, summarize, and plot Generalized Dissimilarity Models and to make predictions (in both space and time) and map biological patterns by transforming environmental predictor variables. Future updates will incorporate support for genomic data.

The functions in the gdm package provide the tools necessary for fitting GDMs, including functions to prepare biodiversity and environmental data. Major functionality includes:

Formatting various types of biodiversity and environmental data to gdm's site-pair format used in model fitting

Fitting GDMs using geographic and environmental distances between sites

Plotting fitted functions & extracting I-spline values

Predicting pairwise dissimiliarites between sites or times and transforming envirnmental predictors to biological importance and mapping these patterns.

To see the preferable citation of the package, type `citation("gdm")`

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GDM fits biological distances to pairwise site geographical and environmental distances. Most users will need to first format their data to gdm's site-pair table format:

`formatsitepair` | To convert biodiversity and environmental data to site-pair format |

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`gdm` | To fit a GDM model |

`summary` | To summarize a GDM model |

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`predict` | To predict biological dissimilarities between sites in space or between time periods |

`gdm.transform` | To transform each environmental predictor to biological importance |

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`plot` | To plot model fit and I-splines |

`isplineExtract` | To extract I-spline values to allow for custom plotting |

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The gdm development team is Glenn Manion, Matt Lisk, Simon Ferrier, Diego Nieto-Lugilde, and Matt Fitzpatrick. Where others have contributed to individual functions, credits are provided in function help pages.

The maintainers of the R version of gdm are Matt Fitzpatrick <[email protected]> and Matt Lisk <[email protected]>.

gdm documentation built on June 6, 2018, 1:04 a.m.

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